Progress in the selection of production traits in the poultry industry has been dramatic over the past 75 years. Genetic progress has its biological limits and these may be reached in the next 20 years. The poultry industry will need to adapt with more emphasis on the needs of the consumer (e.g. product quality, health and animal welfare), as well as the needs of the breeders/producers (e.g. lower feed costs and higher fertility). These new traits are difficult and costly to measure by conventional genetic selection methods - the application of genomics is a possible solution. Poultry genomics has benefited from the rapid technological advances in the genetics of model organisms and human. A number of resources and approaches are now well established, including genetic markers and maps (both genetic and physical), QTL mapping, comparative mapping, EST and BAC resources. In addition, the next phase of gene discovery - Functional Genomics is underway. How the poultry industry can benefit and get access to these new technologies is discussed.

The initiation of genome projects on helminths of medical importance promises to yield new drug targets and vaccine candidates in unprecedented numbers. In order to exploit this emerging data it is essential that the user community is aware of the scope and quality of data available, and that the genome projects provide analyses of the raw data to highlight potential genes of interest. Core bioinformatics support for the parasite genome projects has promoted these approaches. In the Brugia genome project, a combination of expressed sequence tag sequencing from multiple cDNA libraries representing the complete filarial nematode lifecycle, and comparative analysis of the sequence dataset, particularly using the complete genome sequence of the model nematode C. elegans, has proved very effective in gene discovery.

The genetic diversity of most livestock species is reducing and it is not possible to preserve all livestock breeds. In order to preserve as much of the genetic diversity as possible we must first have a robust method of measuring the genetic differences between breeds. The analysis of microsatellite allele frequency is now the method of choice. Using sheep as an example, this paper describes the methods used for both microsatellite amplification and the analysis of the data once it has been collected.